Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques

Written for practicing engineers and graduate students, this text brings together adaptive control with neural networks and fuzzy systems for the control of nonlinear systems. The authors present a control methodology that may be verified with mathematical rigor while possessing the flexibility and ease of implementation associated with intelligent control approaches. Design techniques are presented for nonlinear multi-output systems in state-feedback, output-feedback, continuous or discrete-time, and decentralized form.